Strands just open-sourced Decider 2B, a small model built strictly for fast decision-making rather than chatting. Built on a Qwen3.5-2B backbone with a custom pointer head, it picks between predefined options with confidence scores in a median 115ms on an RTX 3090. Why it matters: It gives local agents cheap, reliable guardrails before firing expensive LLM calls.
NemoStation just open-sourced Marlin-2B, a 2B vision-language model fine-tuned from Qwen 3.5 built to extract structured video data. It answers what happened and exactly when, generating timestamps and boundaries that rival far larger models. Why it matters: you can now run fast, local video search and dense captioning directly on your machine without paying API fees.
Alibaba's Qwen team just launched the Qwen3.5 Small Model Series, offering four compact sizes from 0.8B to 9B parameters along with base checkpoints. Built with native multimodal architecture and scaled reinforcement learning, the lineup aims to deliver snappy intelligence directly on edge devices and local agents.
